Search - fuzzy-c-cluster

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【Linux-Unix】 mohuC DL : 0: UNIX下使用的基于模糊Ｃ聚类分析的原码-use of UNIX-based C Fuzzy Cluster Analysis of the original code
Update : 2008-10-13 Size : 957540 Publisher : 腾飞
【AI-NN-PR】 fuzzy_cluster_analysis.tar DL : 0: 模糊聚類分析源碼。包含教學文件，C源碼，實驗資料-Fuzzy Cluster Analysis source. Includes teaching document, C source code, experimental data
Update : 2024-05-19 Size : 541696 Publisher : allen
【CSharp】 FCM DL : 0: fuzzy cluster method by c#
Update : 2024-05-19 Size : 591872 Publisher : 余翔宇
【File Format】 9552010E202 DL : 0: This paper presents a new cluster validity index for nding a suitable number of fuzzy clusters with crisp and fuzzy data. The new index, called the ECAS-index, contains exponential compactness and separation measures. These measures indicate homogeneity within clusters and heterogeneity between clusters, respectively. Moreover, a fuzzy c-mean algorithm is used for fuzzy clustering with crisp data, and a fuzzy k-numbers clustering is used for clustering with fuzzy data. In comparison to other indices, it is evident that the proposed index is more effective and robust under different conditions of data sets, such as noisy environments and large data sets.
Update : 2024-05-19 Size : 3467264 Publisher : m
【matlab】 FCMClust DL : 0: 模糊C均值聚类（FCM）算法是一种经典的模糊聚类分析方法，但其算法初始聚类中心集是随机选取的，从而造成算法的性能强烈的依赖聚类中心集的初始化。-Fuzzy C-Means clustering (FCM) algorithm is a classical fuzzy clustering analysis method, but the algorithm sets the initial cluster centers are selected randomly, resulting in a strong dependence on the performance of the algorithm is initialized cluster centers set.
Update : 2024-05-19 Size : 2048 Publisher : 张勤拙
【AI-NN-PR】 Clustering-Algorithms DL : 0: 在众多聚类算法中,基于划分的模糊聚类算法是模式识别中最常用的算法类型之一.至今,文献中仍不断有关于基于划分的模糊聚类算法的研究成果出现.为了能更为系统和深入地了解这些聚类算法及其性质,本文从改变度量方式、改变约束条件、在目标函数中引入熵以及考虑对聚类中心进行约束等几个方面,对在 C-均值算法的基础上得到的基于划分的模糊聚类算法作了综述和评价,对各典型算法的优缺点进行了实验比较分析.指出标准 FCM算法被广泛应用的原因之一是它对数据的比例变化具有鲁棒性,而其他类似的算法对这种比例变化却很敏感, 并以极大熵方法为例进行了比较实验.最后总结了基于划分的模糊聚类算法普遍存在的问题及其发展前景. -Fuzzy partitional clustering algorithms are widely used in pattern recognition field. Until now, more and more research results on them have been developed in the literature. In order to study these algorithms systematically and deeply, they are reviewed in this paper based on c-means algorithm, from metrics, entropy, and constraints on membership function or cluster centers. Moreover, the advantages and disadvantages of the typical fuzzy partitional algorithms are discussed. It is pointed out that the standard FCM algorithm is robust to the scaling transformation of dataset, while others are sensitive to such transformation. Such conclusion is experimentally verified when implementing the standard FCM and the maximum entropy clustering algorithm. Finally, the problems existing in these algorithms and the prospects of the fuzzy partitional algorithms are discussed.
Update : 2024-05-19 Size : 452608 Publisher : 成方
【Special Effects】 fcmMATLAB DL : 0: 模糊C-均值算法容易收敛于局部极小点，为了克服该缺点，将遗传算法应用于模糊C-均值算法(FCM)的优化计算中，由遗传算法得到初始聚类中心，再使用标准的模糊C-均值聚类算法得到最终的分类结果。-Fuzzy C- means algorithm is easy to converge to a local minimum point, in order to overcome this drawback, the genetic algorithm is applied to fuzzy C- means algorithm (FCM) optimization calculations by the genetic algorithm initial cluster centers, and then using standard fuzzy C- means clustering algorithm to obtain the final classification results.
Update : 2024-05-19 Size : 198656 Publisher : 胡丹丹
【matlab】 tiejindu DL : 0: 这是模糊C均值聚类求出聚类中心以后，待检测样本与聚类中心的贴近程度的计算程序-This is the fuzzy C-means clustering obtained after the cluster center, close to the level of the sample to be detected and clustering center calculation program
Update : 2024-05-19 Size : 2048 Publisher : 李媛媛
【Other resource】 FCM DL : 0: 核聚类算法：聚类是将一组给定的未知类标号的样本分成内在的多个类别，使得同一类中的样本具有较高的相似度，而不同类中的样本差别大。侧重于软聚类（模糊C-均值——FCM），但其描述手段同样适合于硬聚类（HCM）等同类问题。-Clustering algorithm: cluster is a group of unknown samples given class label into internal multiple categories, so that the same class The sample has a high degree of similarity, rather than difference in kind in large samples. Focused on the soft clustering (Fuzzy C- Means FCM), but its description means equally suitable for hard poly Class (HCM) and other similar issues.
Update : 2024-05-19 Size : 116736 Publisher : 楚淇博
【AI-NN-PR】 gafcm DL : 0: 这是遗传算法改进的模糊C-均值聚类MATLAB源代码,由遗传算法得到初始聚类中心，再使用标准的模糊C-均值聚类算法得到最终的分类结果。-This is the MATLAB source code of the improved fuzzy c-means clustering(FCM) based on the genetic algorithm(GA).The initial cluster centers are otained through GA,and the final cluster centers are obtained using the standard FCM.
Update : 2024-05-19 Size : 1024 Publisher : 简川霞
【matlab】 FCM DL : 0: Data clustering by using Fuzzy c means, where c means number of cluster, m means weight of membership function matrix, X means data input.
Update : 2024-05-19 Size : 1024 Publisher : yuwen chen
【AI-NN-PR】 FCM.m DL : 0: 使用模糊C均值算法对数据集进行聚类分析，效果良好。(The fuzzy C means algorithm is used to cluster the data sets, and the results are good.)
Update : 2024-05-19 Size : 2048 Publisher : cindy_gao
【matlab】 FCM聚类 DL : 0: FCM聚类分析matlab代码可进行模糊c聚类分析！(FCM clustering analysis of matlab code for C fuzzy cluster analysis!)
Update : 2024-05-19 Size : 11264 Publisher : 晨17
【Graph program】 Fuzringorip DL : 0: Fuzzy clustering algorithms like the popular fuzzy c-means algorithm (FCM) are frequently used to automatically divide up the data space into fuzzy granules. When the fuzzy clusters are used to derive membership functions for a fuzzy rule-based system,then the corresponding fuzzy sets should fulfill some requirements like boundedness of support or unimodality.(Problems may also arise in the case, when the fuzzy partition induced by the clusters is intended as a basis for local function approximation. In this case, a local model (function) is assigned to each cluster. Taking the fuzziness of the partition into account, continuous transitions between the single local models can be obtained easily.)
Update : 2024-05-19 Size : 629760 Publisher : song86
【Special Effects】 2.2 图像分割技术 DL : 0: FCM算法是一种基于划分的聚类算法，它的思想就是使得被划分到同一簇的对象之间相似度最大，而不同簇之间的相似度最小。模糊C均值算法是普通C均值算法的改进，普通C均值算法对于数据的划分是硬性的，而FCM则是一种柔性的模糊划分。在介绍FCM具体算法之前我们先介绍一些模糊集合的基本知识。(The FCM algorithm is a partition-based clustering algorithm. Its idea is to make the similarity among the objects that are divided into the same cluster be the largest, and the similarity between different clusters is the smallest. The fuzzy C-means algorithm is an improvement of the ordinary C-means algorithm. The common C-means algorithm is hard for the data division, and FCM is a flexible fuzzy division. Before introducing the specific FCM algorithm, we first introduce some basic knowledge of fuzzy sets.)
Update : 2024-05-19 Size : 754688 Publisher : EMC
【Other】 fcm DL : 0: 一种快速的抗噪声模糊C均值图像分割算法图像分割就是把图像分成若干个特定的、具有独特性质的区域并提出。该算法结合像素灰度值相似度和隶属度构造了一个新的空间函数。该空间函数用于更新成员关系，而成员关系又用于迭代地获取聚类中心。所提出的算法可以在较少的迭代次数下获得理想的分割结果，有效地降低了噪声的影响。(A fast anti noise Fuzzy C-Means Image Segmentation AlgorithmImage segmentation is to divide the image into several specific, unique areas and propose. In this algorithm, a new spatial function is constructed by combining the similarity and membership of pixel gray value. The spatial function is used to update the membership, and the membership is used to obtain the cluster center iteratively. The proposed algorithm can get ideal segmentation results with less iterations and effectively reduce the impact of noise.)
Update : 2024-05-19 Size : 294912 Publisher : 李咿呀咿呀哟

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